A survey on deep-learning-based lidar 3d object detection for autonomous driving
LiDAR is a commonly used sensor for autonomous driving to make accurate, robust, and fast
decision-making when driving. The sensor is used in the perception system, especially …
decision-making when driving. The sensor is used in the perception system, especially …
Application of deep learning on millimeter-wave radar signals: A review
The progress brought by the deep learning technology over the last decade has inspired
many research domains, such as radar signal processing, speech and audio recognition …
many research domains, such as radar signal processing, speech and audio recognition …
From the semantic point cloud to heritage-building information modeling: A semiautomatic approach exploiting machine learning
This work presents a semi-automatic approach to the 3D reconstruction of Heritage-Building
Information Models from point clouds based on machine learning techniques. The use of …
Information Models from point clouds based on machine learning techniques. The use of …
Learning-based methods of perception and navigation for ground vehicles in unstructured environments: A review
The problem of autonomous navigation of a ground vehicle in unstructured environments is
both challenging and crucial for the deployment of this type of vehicle in real-world …
both challenging and crucial for the deployment of this type of vehicle in real-world …
Recent advancements in learning algorithms for point clouds: An updated overview
Recent advancements in self-driving cars, robotics, and remote sensing have widened the
range of applications for 3D Point Cloud (PC) data. This data format poses several new …
range of applications for 3D Point Cloud (PC) data. This data format poses several new …
Automated digital modeling of existing buildings: A review of visual object recognition methods
Digital building representations enable and promote new forms of simulation, automation,
and information sharing. However, creating and maintaining these representations is …
and information sharing. However, creating and maintaining these representations is …
Wcnn3d: Wavelet convolutional neural network-based 3d object detection for autonomous driving
Three-dimensional object detection is crucial for autonomous driving to understand the
driving environment. Since the pooling operation causes information loss in the standard …
driving environment. Since the pooling operation causes information loss in the standard …
Forest structural complexity tool—an open source, fully-automated tool for measuring forest point clouds
Forest mensuration remains critical in managing our forests sustainably, however, capturing
such measurements remains costly, time-consuming and provides minimal amounts of …
such measurements remains costly, time-consuming and provides minimal amounts of …
Fusionrcnn: Lidar-camera fusion for two-stage 3d object detection
Accurate and reliable perception systems are essential for autonomous driving and robotics.
To achieve this, 3D object detection with multi-sensors is necessary. Existing 3D detectors …
To achieve this, 3D object detection with multi-sensors is necessary. Existing 3D detectors …
Semi-supervised learning-based point cloud network for segmentation of 3D tunnel scenes
Automatic identifying target multi-class objects in tunnel scenes from 3D point clouds is
widely thought to be critical for maintaining the healthy condition of the tunnel using deep …
widely thought to be critical for maintaining the healthy condition of the tunnel using deep …